Inductive Genetic Programming with Immune Network Dynamics
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InCollection{nikolaev:1999:aigp3,
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author = "Nikolay I. Nikolaev and Hitoshi Iba and Vanio Slavov",
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title = "Inductive Genetic Programming with Immune Network
Dynamics",
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booktitle = "Advances in Genetic Programming 3",
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publisher = "MIT Press",
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year = "1999",
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editor = "Lee Spector and William B. Langdon and
Una-May O'Reilly and Peter J. Angeline",
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chapter = "15",
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pages = "355--376",
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address = "Cambridge, MA, USA",
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month = jun,
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-262-19423-6",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/aigp3/ch15.pdf",
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DOI = "doi:10.7551/mitpress/1110.003.0020",
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size = "22 pages",
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abstract = "This chapter presents an immune version of Genetic
Programming (GP). This is a GP version that conducts
progressive search controlled by a dynamic fitness
function. The new fitness function is based on analogy
with a model of the biological immune system, such that
the programs are viewed as lymphocyte clones that
compete to recognize most of the examples, viewed as
antigens. The programs are reinforced with rewards for
matched important examples and stimulated to match
different examples. Examples recognized by a small
number of programs are considered important. The
motivation for using the immune dynamics for GP
navigation is to maintain a high population diversity
and to achieve enhanced search performance. Empirical
evidence for the efficacy of this immune version on
practical inductive machine learning and time-series
prediction tasks is provided",
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notes = "AiGP3 See http://cognet.mit.edu",
- }
Genetic Programming entries for
Nikolay Nikolaev
Hitoshi Iba
Vanio Slavov
Citations